Введение в машинное обучение

Магистратура 2021/2022

Статус: Курс по выбору (Финансовый инжиниринг)

Направление: 38.04.08. Финансы и кредит

Кто читает: Практико-ориентированные магистерские программы факультета экономических наук

Где читается: Факультет экономических наук

Когда читается: 2-й курс, 1 модуль

Формат изучения: с онлайн-курсом

Онлайн-часы: 28

Охват аудитории: для своего кампуса

Преподаватели: Курочкин Сергей Владимирович

Прогр. обучения: Финансовый инжиниринг

Язык: русский

Кредиты: 3

Контактные часы: 2

Полная версия программы учебной дисциплины

Аннотация

This specialization gives an introduction to deep learning, reinforcement learning, natural language understanding, computer vision and Bayesian methods. Top Kaggle machine learning practitioners and CERN scientists will share their experience of solving real-world problems and help you to fill the gaps between theory and practice. Upon completion of 7 courses you will be able to apply modern machine learning methods in enterprise and understand the caveats of real-world data and settings.

Цель освоения дисциплины

The goal of this course is to give learners basic understanding of modern neural networks and their applications in computer vision and natural language understanding.

Планируемые результаты обучения

We'll consider the reinforcement learning formalisms in a more rigorous, mathematical way. You'll learn how to effectively compute the return your agent gets for a particular action - and how to pick best actions based on that return.
We'll find out how to apply last week's ideas to the real world problems: ones where you don't have a perfect model of your environment.
We'll learn to scale things even farther up by training agents based on neural networks.
You'll learn how to build better exploration strategies with a focus on contextual bandit setup